Remove legal privacy
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Responsible AI must-haves for unified observability and security

Dynatrace

There is an increased focus on trusted, responsible AI because when the following factors are overlooked, they can cause significant financial, business, and legal repercussions: The opacity of algorithms. Users are in control of each phase of Davis AI processing to ensure data privacy, eliminate bias, and promote fairness.

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Privacy controls and barriers to session replay

Dynatrace

But session replay privacy and concern about privacy controls have become a barrier to adopting it for many who want to take advantage of its benefits. But concerns about maintaining privacy with session replay tools have made many organizations hesitant to fully adopt them. Examples include the following. Medical data.

Analytics 191
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Privacy spotlight: Retain data in Grail with 1-day precision, for up to 10 years

Dynatrace

Streamline privacy requirements with flexible retention periods Data retention is a critical aspect of data handling, and it’s not just about privacy compliance—it’s about having the flexibility to optimize data storage times in Grail for your Dynatrace use cases.

Storage 166
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Keeping data in India with AI-powered observability operated on AWS Mumbai

Dynatrace

This means that Dynatrace customers in India can keep the data of their customers and end users in India and benefit from a comprehensive set of features that support data privacy and security. We identified the following requirements for customers that necessitate hosting the Dynatrace platform in India: Legal regulations.

AWS 238
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Stay in control of your data retention with Dynatrace Grail—from 10 days to 10 years

Dynatrace

Customer decisions about data retention are often determined by important security, privacy, and legal issues. This is the case when a company no longer has legal grounds to retain its customer data, as outlined in privacy protection regulations.

Analytics 213
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15 Best Practices on API Security for Developers

DZone

Compliance and regulatory requirements : Many industries, such as finance, healthcare, and government, have strict regulatory requirements for data security and privacy. Developers must ensure that their APIs comply with these standards, such as GDPR, HIPAA, or PCI-DSS, to avoid legal and financial penalties.

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The path to achieving unprecedented productivity and software innovation through ChatGPT and other generative AI

Dynatrace

Establishing guardrails to protect intellectual property and data privacy As DevOps and platform engineering teams use GPTs to accelerate software development, site reliability engineers (SREs) and privacy teams must ensure these technologies have the proper controls to avoid creating more problems than those they’re solving.